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筑波大学｜University of Tsukuba / Exchange Student
I graduated from Zhejiang University and now I am in University of Maryland for a Master. Recently, I am interested and studying about data and business, and looking for full-time job position on those areas.
As a great game lover and anime fan, I really proficient about Japanese entertainment culture, and would love to join an entertainment company in Japan or China.
Project: Airbnb.com Prediction Contest; Identify and Rank Top Competitors using Microsoft SQL Server; Identify and Rank Top Competitors using Microsoft SQL Server Courses: Big Data and AI; Data Mining; Database; Project Management; Applied Finance Information Systems
• Contributed in a growth hacker team of six. Merged data from databases, surveyed key values of competitors and visualized data aiding to make business strategies. • Operated text mining skills to investigated valuable points from thousands of reviews in application stores.
Projects: Research on the Influence of Time Perception to Working Memory; Research on the Influence of Consumption Courses: Statistics; Experimental Psychology; Applied Experimental Psychology Activities: Key Member in School Official Chorus
Studied Japanese and Japanese Culture
• Developed on a team of four an end-to-end front and back-end dynamic system to rank and report top industry competitors using Microsoft SQL Server and ER diagramming tools, 54 rows and 20 features of industry ranking data. • Designed and wrote innovative webpage as front-end leveraging html and CSS; ensured on time delivery of project.
• Created a team of five to examine strategic application of IT investment strategy of a firm targeted for potential investment. • Performed SWOT, VRIN and market research using Hoovers and other industry resources to make an investment recommendation based in part on Strategic IT capabilities.
• Collaborated with team of five to predict review scores rating of Airbnb.com, using a listing of training data with 100,000 objects, 70 features. • Led data cleaning and preprocessing; developed sub models using random forest, linear regression, KNN to predict review scores rating – achieved final RMSE of 6.9.
筑波大学｜University of Tsukuba / Exchange Student
• Collaborated with team of five to predict review scores rating of Airbnb.com, using a listing of training data with 100,000 objects, 70 features. • Led data cleaning and preprocessing; developed sub models using random forest, linear regression, KNN to predict review scores rating – achieved final RMSE of 6.9.
